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Albert Large V2 Finetuned Rte
This model is a text classification model fine-tuned on the GLUE RTE task based on ALBERT-large-v2, used for recognizing textual entailment relationships.
Downloads 22
Release Time : 3/2/2022
Model Overview
This is a fine-tuned ALBERT model specifically designed for Textual Entailment tasks, determining whether a premise text entails a hypothesis text.
Model Features
Based on ALBERT Architecture
Utilizes the ALBERT-large-v2 architecture with optimized features like parameter sharing.
GLUE RTE Task Fine-tuning
Specifically optimized for the Textual Entailment Recognition task in the GLUE dataset.
Lightweight Model
Compared to the original BERT model, the ALBERT architecture is more lightweight and efficient.
Model Capabilities
Text Classification
Textual Entailment Recognition
Natural Language Understanding
Use Cases
Natural Language Processing
Textual Entailment Judgment
Determines whether a given premise text entails a hypothesis text.
Achieves 54.87% accuracy on the GLUE RTE task.
Question Answering System Support
Assists question-answering systems in determining whether an answer is entailed in the given text.
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